Low-cost grain sorting technologies to reduce mycotoxin contamination in maize and groundnut

A review on mycotoxins and mycotoxicoses in ruminants and Equidae in South America

Of the mycotoxicoses caused by molds contaminating grains or their byproducts, leukoencephalomalacia of horses and less frequently aflatoxicosis in cattle have been reported in South America. However, the most important group of mycotoxins in the region are those caused by fungi that infect forages and other types of plants and have regional distribution. In this group, ergotism is important, both caused by Claviceps purpurea infecting grains or by Epichloë coenophiala infecting Schedonorus arundinaceus. Other important mycotoxicoses are those caused by indole-diterpenes produced by Clavicipitaceous fungi including Claviceps paspali in Paspalum spp., Claviceps cynodontes in Cynodon dactylon, and by Periglandula a seed transmitted symbiont associated with the tremorgenic plant Ipomoea asarifolia. The latter is an important poisoning in the northeastern and northern Brazil. Other important mycotoxicoses are those caused by swainsonine containing plants. It was demonstrated that swainsonine contained in Ipomoea carnea var. fistulosa is produced by an epibiotic fungus of the order Chaetothyriales whose mycelia develop on the adaxial surface of the leaves. Swainsonine is also produced by the symbiotic, endobiotic fungi Alternaria section Undifilum spp., which is associated with Astragalus spp. in the Argentinian Patagonia causing poisoning. Another form of mycotoxicosis occurs in poisoning by Baccharis spp., mainly B. coridifolia, a very important toxic plant in South America that contains macrocyclic trichothecenes probably produced by an endophytic fungus that has not yet been identified. Pithomycotoxicosis caused by Pithomyces chartarum used to be an important mycotoxicosis in the region, mainly in cattle grazing improved pastures of legumes and grasses. Slaframine poisoning, diplodiosis and poisoning by barley contaminated by Aspergillus clavatus has been rarely diagnosed in Brazil, Uruguay and Argentina.

Processing complementary foods to reduce mycotoxins in a medium scale Tanzanian mill: A hazard analysis critical control point (HACCP) approach

Designing and implementing processing procedures for producing safe complementary foods in dynamic and unregulated food systems where common food staples are frequently contaminated with mycotoxins is challenging. This paper presents lessons about minimizing aflatoxins (AF) in groundnut flour and AF and/or fumonisins (FUM) in maize and groundnut pre-blended flour for complementary feeding in the context of a dietary research intervention in rural Tanzania. The flours were processed in collaboration with Halisi Products Limited (Halisi), a medium scale enterprise with experience in milling cereal-based flours in Arusha, Tanzania. Using a hazard analysis critical control point (HACCP) approach for quality assurance, two critical control points (CCPs) for AF in processing the pre-blended flour were identified: 1) screening maize before procurement, and 2) blending during the processing of each constituent flour. Blending of maize flour was also identified as a CCP for FUM. Visual inspection during screening and sorting were identified as important control measures for reducing AF, but these steps did not meet the criteria for a CCP due to lack of objective measurement and verifiable standards for AF. The HACCP approach enabled the production of low AF (<5 μg/kg) and FUM (<2 μg/g) flours with low rejection rates for the final products. The paper presents practical lessons that could be of value to a range of commercial processors in similar low- and middle-income contexts who are keen on improving food quality.

Zearalenone contamination in maize, its associated producing fungi, control strategies, and legislation in Sub-Saharan Africa

The fungal genus Fusarium contains many important plant pathogens as well as endophytes of wild and crop plants. Globally, Fusarium toxins in food crops are considered one of the greatest food safety concerns. Their occurrence has become more pronounced in Africa in recent times. Among the major Fusarium mycotoxins with food and feed safety concerns, zearalenone is frequently detected in finished feeds and cereals in Africa. However, the impact of indigenous agricultural practices (pre- and postharvest factors) and food processing techniques on the prevalence rate of Fusarium species and zearalenone occurrence in food and feed have not been collated and documented systematically. This review studies and analyzes recent reports on zearalenone contamination in maize and other cereal products from Africa, including its fungi producers, agronomic and climate variables impacting their occurrences, preventive measures, removal/decontamination methods, and legislations regulating their limits. Reports from relevant studies demonstrated a high prevalence of F. verticillioides and F. graminearum as Africa's main producers of zearalenone. Elevated CO2 concentration and high precipitation may carry along an increased risk of zearalenone contamination in maize. African indigenous processing methods may contribute to reduced ZEA levels in agricultural products and foods. Most African countries do not know their zearalenone status in the food supply chain and they have limited regulations that control its occurrence.

One stone two birds: Recycling of an agri-waste to synthesize laccase-immobilized hierarchically porous magnetic biochar for efficient degradation of aflatoxin B1 in aqueous solutions and corn oil

Aflatoxin B1 (AFB1) contamination of oils is a serious concern for the safety of edible oil consumers. Enzyme-assisted detoxification of AFB1 is an efficient and safe method for decontaminating oils, but pristine enzymes are unstable in oils and require modifications before use. Therefore, we designed a novel and magnetically separable laccase-carrying biocatalyst containing spent-mushroom-substrate (SMS)-derived biochar (BF). Laccase was immobilized on NH2-activated magnetic biochar (BF-NH2) through covalent crosslinking, which provided physicochemical stability to the immobilized enzyme. After 30 days of storage at 4 °C, the immobilized laccase (product named "BF-NH2-Lac") retained ~95 % of its initial activity, while after five repeated cycles of ABTS oxidation, ~85 % activity retention was observed. BF-NH2-Lac was investigated for the oxidative degradation of AFB1, which exhibited superior performance compared to free laccase. Among many tested natural compounds as mediators, p-coumaric acid proved the most efficient in activating laccase for AFB1 degradation. BF-NH2-Lac demonstrated >90 % removal of AFB1 within 5.0 h, while the observed degradation efficiency in corn oil and buffer was comparable. An insight into the adsorptive and degradative removal of AFB1 revealed that AFB1 removal was governed mainly by degradation. The coexistence of multi-mycotoxins did not significantly affect the AFB1 degradation capability of BF-NH2-Lac. Investigation of the degradation products revealed the transformation of AFB1 into non-toxic AFQ1, while corn oil quality remained unaffected after BF-NH2-Lac treatment. Hence, this study holds practical importance for the research, knowledge-base and industrial application of newly proposed immobilized enzyme products.

Aflatoxins Contamination in Feed Commodities: From Occurrence and Toxicity to Recent Advances in Analytical Methods and Detoxification

Synthesized by the secondary metabolic pathway in Aspergilli, aflatoxins (AFs) cause economic and health issues and are culpable for serious harmful health and economic matters affecting consumers and global farmers. Consequently, the detection and quantification of AFs in foods/feeds are paramount from food safety and security angles. Nowadays, incessant attempts to develop sensitive and rapid approaches for AFs identification and quantification have been investigated, worldwide regulations have been established, and the safety of degrading enzymes and reaction products formed in the AF degradation process has been explored. Here, occurrences in feed commodities, innovative methods advanced for AFs detection, regulations, preventive strategies, biological detoxification, removal, and degradation methods were deeply reviewed and presented. This paper showed a state-of-the-art and comprehensive review of the recent progress on AF contamination in feed matrices with the intention of inspiring interests in both academia and industry.

Aflatoxins posing threat to food safety and security in Pakistan: Call for a one health approach

Aflatoxins are among the most important mycotoxins due to their widespread occurrence and adverse impacts on humans and animals. These toxins and/or their metabolites cannot be destroyed with cooking or boiling methods. Therefore, consumption of aflatoxin-contaminated food may lead to impaired growth, compromised immunity, stomach and liver cancer, and acute toxicity. These adverse effects along with food wastage might have detrimental consequences on a country's economy. Several studies from Pakistan reported a high prevalence of aflatoxins in food and feed commodities (Range; milk = 0.6-99.4%, cereals, and grains = 0.38-41%, animal feed = 31-100%). Notably, Pakistan reported very high figures of impaired child growth-stunted 40.2%, wasted 17.7% and underweight 28.9%-that could be associated with the higher aflatoxin prevalence in food items. Importantly, high aflatoxins prevalence, i.e. 100%, 69% and 60.5%, in children has been reported in Pakistan. Food and feed are more prone to aflatoxin contamination due to Pakistan's hot and humid climate; however, limited awareness, inadequate policy framework, and weak implementation mechanisms are the major obstacles to effective control. This review will discuss aflatoxins prevalence, associated risk factors, adverse health effects, required regulatory regime, and effective control strategies adopting the One Health approach to ensure food safety and security.

Multispectral Sorting Based on Visibly High-Risk Kernels Sourced from Another Country Reduces Fumonisin and Toxigenic Fusarium on Maize Kernels

Fusarium species infect maize crops leading to the production of fumonisin by their toxigenic members. Elimination of microbes is critical in mitigating further postharvest spoilage and toxin accumulation. The current study investigates the efficacy of a previously described multispectral sorting technique to analyze the reduction of fumonisin and toxigenic Fusarium species found contaminating maize kernels in Kenya. Maize samples (n = 99) were collected from six mycotoxin hotspot counties in Kenya (Embu, Meru, Tharaka Nithi, Machakos, Makueni, and Kitui County) and analyzed for aflatoxin and fumonisin using commercial ELISA kits. Aflatoxin levels in majority (91%) of the samples were below the 10 ng/g threshold set by the Kenya Bureau of Standards and therefore not studied further. The 23/99 samples that had >2,000 ng/g of fumonisin were selected for sorting. The sorter was calibrated using kernels sourced from Ghana to reject visibly high-risk kernels for fumonisin contamination using reflectance at nine distinct wavelengths (470-1,550 nm). Accepted and rejected streams were tested for fumonisin using ELISA, and the presence of toxigenic Fusarium using qPCR. After sorting, there was a significant (p < 0.001) reduction of fumonisin, by an average of 1.8 log ng/g (98%) and ranging between 0.14 and 2.7 log ng/g reduction (28-99.8%) with a median mass rejection rate of 1.9% (ranged 0% to 48%). The fumonisin rejection rate ranged between 0 and 99.8% with a median of 77%. There was also a significant reduction (p = 0.005) in the proportion of DNA represented by toxigenic Fusarium, from a mean of 30-1.4%. This study demonstrates the use of multispectral sorting as a potential postharvest intervention tool for the reduction of Fusarium species and preformed fumonisin. The spectral sorting approach of this study suggests that classification algorithms based on high-risk visual features associated with mycotoxin can be applied across different sources of maize to reduce fumonisin.

Rapid Detection of Single- and Co-Contaminant Aflatoxins and Fumonisins in Ground Maize Using Hyperspectral Imaging Techniques

Aflatoxins and fumonisins, commonly found in maize and maize-derived products, frequently co-occur and can cause dangerous illness in humans and animals if ingested in large amounts. Efforts are being made to develop suitable analytical methods for screening that can rapidly detect mycotoxins in order to prevent illness through early detection. A method for classifying contaminated maize by applying hyperspectral imaging techniques including reflectance in the visible and near-infrared (VNIR) and short-wave infrared (SWIR) regions, and fluorescence was investigated. Machine learning classification models in combination with different preprocessing methods were applied to screen ground maize samples for naturally occurring aflatoxin and fumonisin as single contaminants and as co-contaminants. Partial least squares-discriminant analysis (PLS-DA) and support vector machine (SVM) with the radial basis function (RBF) kernel were employed as classification models using cut-off values of each mycotoxin. The classification performance of the SVM was better than that of PLS-DA, and the highest classification accuracies for fluorescence, VNIR, and SWIR were 89.1%, 71.7%, and 95.7%, respectively. SWIR imaging with the SVM model resulted in higher classification accuracies compared to the fluorescence and VNIR models, suggesting that as an alternative to conventional wet chemical methods, the hyperspectral SWIR imaging detection model may be the more effective and efficient analytical tool for mycotoxin analysis compared to fluorescence or VNIR imaging models. These methods represent a food safety screening tool capable of rapidly detecting mycotoxins in maize or other food ingredients consumed by animals or humans.

Assessing aflatoxin safety awareness among grain and cereal sellers in greater Accra region of Ghana: A machine learning approach

Studies have established high prevalence of aflatoxin contamination in grains and cereals produced in Ghana. Mitigation strategies have focused mainly on capacity building for farmers, agricultural extension officers, bulk distributors and processors to the detriment of the market women who act as the final link between consumers and producers. This study used supervised machine learning algorithms by means of Classification and Regression Trees (CART) to investigate aflatoxin knowledge and awareness of market women in Greater Accra Region of Ghana. A cross-sectional survey and probability sampling methods were employed for data collection. Ninety-two (92%) of participants had never heard about aflatoxins and yet, 62% reported that they usually observe mould growth in their cereals/grains. Unsurprisingly, 97% of participants indicated that they had no knowledge of the aflatoxin bill passed by the government of Ghana parliament. Despite participants not being aware of aflatoxin menace, the percent correctness of their aflatoxin safety measure score was 40%. A regression tree algorithm showed that, participant's ethnic group was the most significant parameter to consider regarding their aflatoxin safety knowledge. Their educational background and age were 95.5% and 72.5% as significant as their ethnic group. A classification tree algorithm showed that, educational level was the most significant parameter to consider when it comes to sorting of grains/cereals. Their ethnic group and marital status were 92.4% and 89.3% as important as educational level. It is therefore imperative for the Ghana government to extend sensitization and awareness programs to these market women, targeting the uneducated and specific age and ethnic groups.

Mycotoxin risk management in maize gluten meal

Maize gluten meal (MGM) is a by-product of maize starch and ethanol, produced by the wet milling process. Its high protein content makes it a preferred ingredient in feed. Given the high prevalence of mycotoxins in maize globally, they pose a significant challenge to use of MGM for feed: wet milling could concentrate certain mycotoxins in gluten components, and mycotoxin consumption affects animal health and can contaminate animal-source foods. To help confront this issue, this paper summarizes mycotoxin occurrence in maize, distribution during MGM production and mycotoxin risk management strategies for MGM through a comprehensive literature review. Available data emphasize the importance of mycotoxin control in MGM and the necessity of a systematic control approach, which includes: good agriculture practices (GAP) in the context of climate change, degradation of mycotoxin during MGM processing with SO2 and lactic acid bacteria (LAB) and the prospect of removing or detoxifying mycotoxins using emerging technologies. In the absence of mycotoxin contamination, MGM represents a safe and economically critical component of global animal feed. With a holistic risk assessment-based, seed-to-MGM-feed systematic approach to reducing and decontaminating mycotoxins in maize, costs and negative health impacts associated with MGM use in feed can be effectively reduced.

A Low-Cost, Portable Device for Detecting and Sorting Aflatoxin-Contaminated Maize Kernels

Aflatoxin contamination of maize is a major food safety issue worldwide. The problem is of special significance in African countries because maize is a staple food. This manuscript describes a low-cost, portable, non-invasive device for detecting and sorting aflatoxin-contaminated maize kernels. We developed a prototype employing a modified, normalized difference fluorescence index (NDFI) detection method to identify potentially aflatoxin-contaminated maize kernels. Once identified, these contaminated kernels can be manually removed by the user. The device consists of a fluorescence excitation light source, a tablet for image acquisition, and detection/visualization software. Two experiments using maize kernels artificially infected with toxigenic Aspergillus flavus were implemented to evaluate the performance and efficiency of the device. The first experiment utilized highly contaminated kernels (71.18 ppb), while mildly contaminated kernels (1.22 ppb) were used for the second experiment. Evidently, the combined approach of detection and sorting was effective in reducing aflatoxin levels in maize kernels. With a maize rejection rate of 1.02% and 1.34% in the two experiments, aflatoxin reduction was achieved at 99.3% and 40.7%, respectively. This study demonstrated the potential of using this low-cost and non-invasive fluorescence detection technology, followed by manual sorting, to significantly reduce aflatoxin levels in maize samples. This technology would be beneficial to village farmers and consumers in developing countries by enabling safer foods that are free of potentially lethal levels of aflatoxins.

[Efficacy of Bright Greenish-Yellow Fluorescence Sorting on Mycotoxin-Contaminated Nutmeg Selection and Characterization of Fungal Flora Related to Mycotoxin Production]

Spices have been known to be highly contaminated commodities with mycotoxins. The Codex Alimentarius reports that nutmeg is particularly contaminated with aflatoxins (AFs) and ochratoxin A (OTA). To eliminate contaminated commodities, visual sorting and bright greenish-yellow fluorescence (BGYF) sorting are used as low-cost technologies in production engineering. In Indonesia, nutmeg is mainly sorted by visual sorting and classified into three grades according to the Indonesian national standards, with importers further defining their own brand as imported products. In this study, we evaluate the efficacy of BGYF sorting as a further selection method to reduce AFs and OTA using the importer's own brand. Further, the level of these mycotoxins and the relationship between fungal flora and mycotoxin contamination were examined. These results showed that BGYF sorting effectively reduces AFs as well as OTA. In addition, BGYF-positive groups were infected by Aspergillus sections Flavi, Nigri, and Circumdati.

Industrial-Scale Cleaning Solutions for the Reduction of Fusarium Toxins in Maize

Grain cleaning is the most effective non-destructive post-harvest mitigation strategy to reduce high levels of mycotoxins on account of the removal of mold-infected grains and grain fractions with high mycotoxin content. In this study, the reduction in the concentration of some co-occurring Fusarium toxins in maize, namely deoxynivalenol (DON), zearalenone (ZEA) and fumonisins B1 and B2 (FBs), was evaluated at an industrial-scale level by mechanical removal (sieving and density separation) of dust, coarse, small, broken, shriveled and low-density kernels and/or optical sorting of defected kernels. Samples were dynamically collected according to the Commission Regulation No. 401/2006 along the entire process line. Mycotoxin analyses of water-slurry aggregate samples were performed by validated LC methods. Depending on the contamination levels in raw incoming maize, the overall reduction rates ranged from 36 to 67% for DON, from 67 to 87% for ZEA and from 27 to 67% for FBs. High levels of DON, ZEA and FBs were found in all rejected fractions with values, respectively, up to 3030%, 1510% and 2680%, compared to their content in uncleaned maize. Results showed that grain cleaning equipment based on mechanical and or optical sorting technologies can provide a significant reduction in Fusarium toxin contamination in maize.

Application of reflectance spectroscopy to identify maize genotypes and aflatoxin levels in single kernels

Spectroscopy is a rapid, non-destructive, and low-cost analytical technique that has the potential to complement more resource-intensive analytical methods. We explored the use of spectral methods to differentiate maize genotypes and assess aflatoxin (AF) contamination in maize kernels. We compared the performance of two instruments: a research-grade ultraviolet-visible-near infrared (UV-Vis-NIR) spectrometer that measures reflectance from 304 -1,085 nm, and a miniaturised NIR spectrometer that measures reflectance from 740-1,070 nm. Both systems were used to predict AF levels in maize kernels from a single genotype and across 10 genotypes, and to predict genotype for the latter. A partial least square discriminant analysis model was trained on 70% of the kernels and tested on the remaining 30%. The classification accuracy for 10 maize genotypes was 71-72% using the UV-Vis-NIR instrument on 1,170 kernels, and 65-66% using the NIR device on 740 kernels. The classification accuracy for 247 AF-contaminated kernels of a single genotype using the UV-Vis-NIR instrument was 71, 82, and 92% for AF thresholds of 20, 100, and 1000 μg/kg, respectively. Using the same spectrometer on 872 kernels from 10 genotypes, AF classification accuracy was 67, 90, and 95% in validation sets for AF thresholds of 20, 100, and 1000 μg/kg, respectively. The UV-Vis-NIR instrument and the NIR device had similar classification accuracies for AF thresholds of 100 and 1000 μg/kg, whereas the NIR device had higher accuracy for the AF threshold of 20 μg/kg. Reflectance spectroscopy outperformed visual sorting and the bright greenish yellow fluorescence test in identifying AF levels. Applying spectral analysis to estimate mycotoxin levels and to identify maize genotypes could contribute to regional toxin surveillance and action efforts. Further, using AF-associated spectral features for grain sorting can reduce AF exposure.

Quantitative detection of Aflatoxin B1 by subpixel CNN regression

Aflatoxin is a highly toxic substance dispersed in peanuts, which seriously harms the health of humans and animals. In this paper, we propose a new method for aflatoxin B1(AFB1) detection inspired by quantitative remote sensing. Firstly, we obtained the relative content of AFB1 at the sub-pixel level by subpixel decomposition (endmember extraction, nonnegative matrix decomposition). Then we modified the transfer learning models (LeNet5, AlexNet, VGG16, and ResNet18) to construct a deep learning regression network for quantitative detection of AFB1. There are 67,178 pixels used for training and 67,164 pixels used for testing. After subpixel decomposition, each aflatoxin pixel was determined to contain content, and each pixel had 400 hyperspectral values (415-799 nm). The experimental results showed that, among the four models, the modified ResNet18 model achieved the best effect, with R² of 0.8898, RMSE of 0.0138, and RPD of 2.8851. Here, we implemented a sub-pixel model for quantitative AFB1 detection and proposed a regression method based on deep learning. Meanwhile, the modified convolution classification model has high predictive ability and robustness. This method provides a new scheme in designing the sorting machine and has practical value.

Validation and Application of a Low-Cost Sorting Device for Fumonisin Reduction in Maize

Fumonisin mycotoxins are a persistent challenge to human and livestock health in tropical and sub-tropical maize cropping systems, and more efficient methods are needed to reduce their presence in food systems. We constructed a novel, low-cost device for sorting grain, the “DropSort”, and tested its effectiveness on both plastic kernel models and fumonisin-contaminated maize. Sorting plastic kernels of known size and shape enabled us to optimize the sorting performance of the DropSort. The device sorted maize into three distinct fractions as measured by bulk density and 100-kernel weight. The level of fumonisin was lower in the heaviest fractions of maize compared to the unsorted samples. Based on correlations among fumonisin and bulk characteristics of each fraction, we found that light fraction 100-kernel weight could be an inexpensive proxy for unsorted fumonisin concentration. Single kernel analysis revealed significant relationships among kernel fumonisin content and physical characteristics that could prove useful for future sorting efforts. The availability of a low-cost device (materials~USD 300) that can be used to reduce fumonisin in maize could improve food safety in resource-limited contexts in which fumonisin contamination remains a pressing challenge.

Aflasafe SN01 is the First Biocontrol Product Approved for Aflatoxin Mitigation in Two Nations, Senegal and The Gambia

Aflatoxin contamination is caused by Aspergillus flavus and closely related fungi. In The Gambia, aflatoxin contamination of groundnut and maize, two staple and economically important crops, is common. Groundnut and maize consumers are chronically exposed to aflatoxins, sometimes at alarming levels, and this has severe consequences on their health and productivity. Aflatoxin contamination also impedes commercialization in local and international premium markets. In neighboring Senegal, an aflatoxin biocontrol product containing four atoxigenic isolates of A. flavus, Aflasafe SN01, has been registered and is approved for commercial use in groundnut and maize. We detected that the four genotypes composing Aflasafe SN01 are also native to The Gambia. The biocontrol product was tested during two years in 129 maize and groundnut fields and compared with corresponding untreated fields cropped by smallholder farmers in The Gambia. Treated crops contained up to 100% less aflatoxins than untreated crops. A large portion of the crops could have been commercialized in premium markets due to the low aflatoxin content (in many cases no detectable aflatoxins), both at harvest and after storage. Substantial aflatoxin reductions were also achieved when commercially produced groundnut received treatment. Here we report for the first time the use and effectiveness of an aflatoxin biocontrol product registered for use in two nations. With the current scale-out and -up efforts of Aflasafe SN01, a large number of farmers, consumers, and traders in The Gambia and Senegal will obtain health, income, and trade benefits.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Mycotoxins contamination of market maize and the potential of density sorting in reducing exposure in unregulated food systems in Kenya

Aflatoxins and fumonisins commonly contaminate key food staples in tropical countries, causing recurring acute and chronic public health problems. The present study was conducted to assess the potential of a simple device designed for density-based sorting of maize for its potential to reduce aflatoxins and fumonisins in diverse samples of naturally contaminated maize. A cross sectional survey was conducted, analysing market maize samples (n=204) from eight counties in Western Kenya. A quarter (25%) of the maize samples were contaminated with aflatoxin B1 above the legal limit of 5 μg/kg and nearly half (48%) were contaminated with fumonisins at levels above the legal limit of 2 μg/g. Analysis of additional samples (n=24) from Meru County showed that contamination of maize with the two toxins was also common in Eastern Kenya. A simple density sorter was used to separate grain samples into heavy and light fractions. With an out-sort rate of 31%, density sorting was effective in separating maize by bulk density and 100-kernel weight (P<0.001). Bulk density was negatively correlated with aflatoxins in unsorted (r=-0.20, P<0.01) and heavy fractions (r=-0.32, P<0.01). Density sorting was effective at reducing fumonisins; for maize samples with >1 μg/g, the heavy (accepted) fraction had 66% lower fumonisins than the unsorted maize. After density sorting, the light and heavy fractions fumonisin levels differed by an average of 8.38 μg/g (P<0.001). However, sorting was not effective at significantly reducing aflatoxin levels in maize that was highly contaminated. A simple density sorting equipment that could be adopted by local small-scale millers has potential to reduce fumonisins in maize. Additional and complementary sorting technologies, such as size screening and spectral sorting might improve the effectiveness of reducing aflatoxins in maize.